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stat.CO2026
Jensen-Bregman split Gibbs sampling
Nicolas Dobigeon, Mame Diarra Fall, Eric Barat
Split Gibbs sampling (SGS) is a versatile tool to sample from complex posterior distributions, such as those arising in imaging inverse problems. However, existing SGS instances ar…
stat.CO2025
Bregman geometry-aware split Gibbs sampling for Bayesian Poisson inverse problems
Elhadji Cisse Faye, Mame Diarra Fall, Nicolas Dobigeon +1
This paper proposes a novel Bayesian framework for solving Poisson inverse problems by devising a Monte Carlo sampling algorithm which accounts for the underlying non-Euclidean geo…